Internet addiction and residual depressive symptoms among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic: a network analysis perspective

Author:

Cai HongORCID,Zhao Yan-Jie,He Fan,Li Shu-Ying,Li Zong-Lei,Zhang Wu-Yang,Zhang Yao,Cheung Teris,Ng Chee H.ORCID,Sha Sha,Xiang Yu-TaoORCID

Abstract

AbstractTo assess the inter-relationships between residual depressive symptoms (RDS) and Internet addiction (IA) using network analysis among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic. RDS and IA were assessed using the Patient Health Questionnaire-9 (PHQ-9) and the Internet Addiction Test (IAT), respectively. Central symptoms and bridge symptoms in the network model were examined. A total of 1,454 adolescents met the study criteria and were included in the analyses. The prevalence of IA was 31.2% (95% CI: 28.8%-33.6%). In the network analysis, the nodes IAT15 (“Preoccupation with the Internet”), PHQ2 (“Sad mood”), and PHQ1 (“Anhedonia”) were the most central symptoms in the IA-RDS network model. Bridge symptoms included IAT10 (“Sooth disturbing about your Internet use”), PHQ9 (“Suicide ideation”), and IAT3 (“Prefer the excitement online to the time with others”). Additionally, PHQ2 (“Sad mood”) was the main node linking “Anhedonia” to other IA clusters. Internet addiction was common among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic. Core and bridge symptoms identified in this study could be prioritized as targets for the prevention and treatment of IA in this population.

Funder

National Natural Science Foundation of China

Universidade de Macau

Publisher

Springer Science and Business Media LLC

Subject

Biological Psychiatry,Cellular and Molecular Neuroscience,Psychiatry and Mental health

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